Discrimination of mesoscale convective system environments using sounding observations

The prediction of the strength of mesoscale convective systems (MCSs), particularly those that produce derechos, is a major concern to operational meteorologists and the lives of the general public. To address this forecast problem, this study examines meteorological variables derived from sounding observations that are found to discriminate among quasi-linear MCSs of different intensities, from derecho-producing systems, to systems that produce no severe surface winds. A set of 188 soundings that sampled the beginning and matures stages of the MCSs are grouped into three categories based on their production of severe surface winds.

Mean low- to upper-level wind speeds and deep-layer vertical wind shear are excellent discriminators among all three categories, while low-level shear and low-level mean wind speeds are not. However, low-level inflow relative to the system is found to be an excellent discriminator, largely because of the strong relationship of system severity to system speed. Examination of the mean wind vectors relative to MCS motion provides evidence that cell propagation along the direction of cell advection is a trait that separates severe, long-lived MCSs from the slower moving, non-severe variety, confirming the relationships described by the Corfidi vector technique. Mid-level environmental lapse rates were found to be very good discriminators between all three MCS categories, while vertical differences in equivalent potential temperature and CAPE only discriminate well between weak and severe/derecho MCS environments. Knowledge of these variables and their distribution among the different categories of MCS intensity can be used to improve forecasts and convective watches of organized convective wind events.